This section presents the performance evaluation of the proposed ENet. A total of 150,000 CSI samples generated with the COST 2100 indoor channel model [1]} at 5.3 GHz is used to validate our method and we divide the training, validation and test sets to contain 100,000, 30,000, 20,000 samples, respectively. In practical applications, the training data can be obtained either through computer simulations by generating CSI samples according to 3GPP channel models or by conducting offline channel measurements. \(N_{\rm {t}}=32\)  antennas is placed at the BS with a uniform linear array (ULA) and \(N_{\rm {c}}=1024\)  subcarriers are assumed. After the angular-delay domain transformation, \(N_{\rm {cc}}=32\)  rows of \({\bf {H}}_{\rm {s}}\)  in the delay domain are reserved. \({\bf {H}}_{\rm {R}}\)  and \({\bf {H}}_{\rm {I}}\)  are normalized. The Adam optimizer is used for the network training with a batch size of 1,000.
<TABLE><FIGURE><FIGURE>